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Part 1: Document Description
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Citation |
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Title: |
Replication data for: The Dangers of Extreme Counterfactuals |
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Identification Number: |
doi:10.7910/DVN/MJ1YCL |
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Distributor: |
Harvard Dataverse |
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Date of Distribution: |
2007-11-28 |
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Version: |
5 |
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Bibliographic Citation: |
King, Gary; Zeng, Langche, 2007, "Replication data for: The Dangers of Extreme Counterfactuals", https://doi.org/10.7910/DVN/MJ1YCL, Harvard Dataverse, V5, UNF:3:ytKKNjK+yR8Pq3H0RcV6eg== [fileUNF] |
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Citation |
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Title: |
Replication data for: The Dangers of Extreme Counterfactuals |
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Identification Number: |
doi:10.7910/DVN/MJ1YCL |
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Authoring Entity: |
King, Gary (Harvard University) |
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Zeng, Langche (UC San Diego) |
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Date of Production: |
2006 |
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Distributor: |
Harvard Dataverse |
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Distributor: |
Harvard Dataverse |
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Date of Deposit: |
2006 |
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Date of Distribution: |
2006 |
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Holdings Information: |
https://doi.org/10.7910/DVN/MJ1YCL |
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Study Scope |
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Keywords: |
Social Sciences |
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Abstract: |
We address the problem that occurs when inferences about counterfactuals -- predictions, "what if" questions, and causal effects -- are attempted far from the available data. The danger of these extreme counterfactuals is that substantive conclusions drawn from statistical models that fit the data well turn out to be based largely on speculation hidden in convenient modeling assumptions that few would be willing to defend. Yet existing statistical strategies provide few reliable means of identifying extreme counterfactuals. We offer a proof that inferences farther from the data are more model-dependent, and then develop easy-to-apply methods to evaluate how model-dependent our answers would be to specified counterfactuals. These methods require neither sen sitivity testing over specified classes of models nor evaluating any specific modeling assumptions. If an analysis fails the simple tests we offer, then we know that substantive results are sensitive to at least some modeling choices that are not based on empirical evidence. <br /> <br /> See also: <a href= "http://gking.harvard.edu/category/research-interests/methods/causal-inference" target="_blank">Casual Inference</a> |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Notes: |
This dataset is made available without information on how it can be used. You should communicate with the Contact(s) specified before use. |
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Other Study Description Materials |
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Related Publications |
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Citation |
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Title: |
King, Gary, and Langche Zeng. 2006. The Dangers of Extreme Counterfactuals. Political Analysis 14: 131–159: <a href= "http://j.mp/iJ7KVv" target="_blank">Link to article</a> |
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Bibliographic Citation: |
King, Gary, and Langche Zeng. 2006. The Dangers of Extreme Counterfactuals. Political Analysis 14: 131–159: <a href= "http://j.mp/iJ7KVv" target="_blank">Link to article</a> |
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File Description--f101364 |
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File: sf.tab |
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Notes: |
UNF:3:ytKKNjK+yR8Pq3H0RcV6eg== |
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The state failure data set |
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List of Variables: | |
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Variables |
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f101364 Location: |
Variable Format: numeric Notes: UNF:3:N1a4mhg91mYPJI/1jZ2gWA== |
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f101364 Location: |
Variable Format: numeric Notes: UNF:3:dgHhL61f796RA9SM2KBlsA== |
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f101364 Location: |
Variable Format: numeric Notes: UNF:3:xL0QHnuvtOmp/ZQonIXPKw== |
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f101364 Location: |
Variable Format: numeric Notes: UNF:3:szdxnBR3DNQPzxfGCalqhA== |
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f101364 Location: |
Variable Format: numeric Notes: UNF:3:6sHEUlqq/ua1J5rRZscQgg== |
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f101364 Location: |
Variable Format: numeric Notes: UNF:3:c5a5Oxrl4w2c9dxld0S+QA== |
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f101364 Location: |
Variable Format: numeric Notes: UNF:3:3wSrJvmkQA4YWoYQqAz3nA== |
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f101364 Location: |
Variable Format: numeric Notes: UNF:3:39A1BbWb3IXb8CF+JUZdbw== |
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f101364 Location: |
Variable Format: numeric Notes: UNF:3:LUTKzTUUimZp0Oj9P/8ZTQ== |
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f101364 Location: |
Variable Format: numeric Notes: UNF:3:U8ffCNoGBT+ad7ghY78lkg== |
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f101364 Location: |
Variable Format: numeric Notes: UNF:3:YNsVvPkK+ZiOYR+3OWYkQQ== |
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f101364 Location: |
Variable Format: numeric Notes: UNF:3:CNxnpCEXh7Ahksj51oCltA== |
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f101364 Location: |
Variable Format: numeric Notes: UNF:3:ERHYhrVdycTfWQeZsgqpxA== |
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Label: |
counterf_eg.out |
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Text: |
Contains the output file |
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Notes: |
text/plain; charset=US-ASCII |
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Label: |
counterf_eg.R |
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Text: |
R code checking hull membership of the 4 counterfactual examples, as well as Haiti counterfactuals |
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Notes: |
text/plain; charset=US-ASCII |
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Label: |
DangersArticle.pdf |
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Text: |
Original Article for this Study: The Dangers of Extreme Counterfactuals |
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Notes: |
application/pdf |
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Label: |
readme.txt |
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Text: |
Detailed information about the files in this study |
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Notes: |
text/plain; charset=US-ASCII |
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Label: |
sf.dist.R |
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Text: |
R code computing Gower distance related measures for all counterfactuals |
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Notes: |
text/plain; charset=US-ASCII |
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Label: |
sf.dta |
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Text: |
The state failure data set, stata format |
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Notes: |
application/x-stata |
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Label: |
sf.hull.R |
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Text: |
File to check convex hull membership of all counterfactuals |
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Notes: |
text/plain; charset=US-ASCII |
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Label: |
sf.out |
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Text: |
The output resulting from sourcing sf.dist.R and then sf.R |
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Notes: |
text/plain; charset=US-ASCII |
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Label: |
sf.R |
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Text: |
File that obtains data for table 1 |
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Notes: |
text/plain; charset=US-ASCII |